Rice (Oryza sativa L.) stands as a vital staple crop with extensive cultivation areas worldwide. Ensuring its stable high-yield production is paramount for food security. However, rice faces persistent threats from multiple pests and diseases throughout its growth cycle, significantly compromising yield and quality. Major threats include rice leaf rollers (Cnaphalocrocis medinalis), planthoppers (brown planthopper Nilaparvata lugens, white-backed planthopper Sogatella furcifera, and small brown planthopper Laodelphax striatellus), and sheath blight caused by Rhizoctonia solani. Yield losses can reach 10%-40% under severe infestation. Traditional control methods often suffer from inefficiency, chemical overuse, and environmental disruption. Recent advancements highlight agricultural drones (UAVs) as transformative tools offering operational simplicity, high efficiency, uniform spray distribution, strong penetration, and enhanced environmental safety.
Materials and Methods
Experimental Site
The field trial was conducted on flat terrain with uniform red clay soil in Hunan Province, China (112°42’05″E, 28°03’47″N, elevation: 83.37 m). The site featured excellent irrigation and drainage with minimal surrounding obstacles.
Materials
- Rice Variety: ‘Taiyou 390’
- Agrochemicals: 25% pymetrozine WP (planthoppers), 20% chlorantraniliprole SC (leaf rollers), 30% benzoyl-propiconazole EC (sheath blight)
- Spray Equipment: DJI T25 agricultural drone (20L tank, LX8060SZ nozzles) vs. electric knapsack sprayer (18L capacity)
Key parameters of the agricultural UAV are detailed in Table 1.
| Effective Swath (m) | Nozzle Quantity | Flow Rate per Nozzle (L/min) | Total Flow Rate (L/min) | Max Payload (L) | Operational Speed (m/s) | Flight Height (m) |
|---|---|---|---|---|---|---|
| 4-7 | 2 | 0-12 | 16 | 20 | 5-6 | 3 |
Experimental Design
Three treatments were established:
- T1: Agricultural drone spraying (6,667 m²)
- T2: Electric knapsack sprayer application (2,000 m²)
- CK: Untreated control (667 m²)
Physical barriers prevented treatment interference. Rice was transplanted at 16,700 hills/667m² with standardized fertilization. Agrochemicals were applied uniformly on August 28 using equivalent active ingredients. The agricultural UAV operated at 5 m/s speed, 3 m height, and 5 m swath. Application volumes were:
- UAV (T1): 2 L/667m²
- Knapsack (T2): 36 L/667m²
The UAV’s downward airflow enhances droplet penetration into the rice canopy, as shown during field operations:
Assessment Methods
Data collection followed standardized protocols:
- Planthoppers: Parallel jump sampling (10 points, 5 hills/point). Insects dislodged into water counted pretreatment and 3, 7, 14 days post-application (DPA). Control efficacy calculated as:
$$ \text{Insect Reduction Rate (\%)} = \frac{\text{Pretreatment Count} – \text{Post-treatment Count}}{\text{Pretreatment Count}} \times 100 $$
$$ \text{Relative Efficacy (\%)} = \left[1 – \frac{\text{Treated Post-Count} \times \text{Control Pre-Count}}{\text{Treated Pre-Count} \times \text{Control Post-Count}}\right] \times 100 $$ - Leaf Rollers: Parallel jump sampling (10 points, 2 hills/point). Live larvae, total leaves, and rolled leaves counted. Leaf roll rate calculated:
$$ \text{Leaf Roll Rate (\%)} = \frac{\text{Rolled Leaves}}{\text{Total Leaves}} \times 100 $$ - Sheath Blight: Diagonal 5-point sampling (5 hills/point). Disease severity graded (0-9 scale):
$$ \text{Disease Index} = \frac{\sum (\text{Grade} \times \text{Number of Plants})}{\text{Total Plants} \times 9} \times 100 $$
$$ \text{Control Efficacy (\%)} = \left[1 – \frac{\text{Treated Post-Index} \times \text{Control Pre-Index}}{\text{Treated Pre-Index} \times \text{Control Post-Index}}\right] \times 100 $$
Phytotoxicity and operational efficiency/cost were recorded.
Results
Planthopper Control
Agricultural UAV application demonstrated superior early efficacy against planthoppers (Table 2). By 14 DPA, both methods achieved complete control.
| Treatment | Pre-Treatment Count | 3 DPA | 7 DPA | 14 DPA | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Live Insects | Reduction (%) | Efficacy (%) | Live Insects | Reduction (%) | Efficacy (%) | Live Insects | Reduction (%) | Efficacy (%) | ||
| T1 (UAV) | 67 | 22 | 67.16 | 89.31 | 2 | 97.01 | 99.02 | 0 | 100 | 100 |
| T2 (Knapsack) | 84 | 47 | 44.05 | 81.79 | 2 | 97.62 | 99.22 | 0 | 100 | 100 |
| CK | 55 | 169 | -207.27 | – | 167 | -203.64 | – | 174 | -216.36 | – |
Leaf Roller Control
Knapsack spraying showed slightly higher early larval reduction (3 DPA), but UAV application achieved the lowest leaf roll rate by 14 DPA (Table 3). Both methods reached 100% larval reduction by 7 DPA.
| Treatment | Pre-Treatment Count | 3 DPA | 7 DPA | 14 DPA | |||||
|---|---|---|---|---|---|---|---|---|---|
| Live Larvae | Reduction (%) | Efficacy (%) | Live Larvae | Reduction (%) | Efficacy (%) | Leaf Roll Rate (%) | Rolled Leaves | ||
| T1 (UAV) | 47 | 31 | 34.04 | 27.86 | 0 | 100 | 100 | 0.28 | 6 |
| T2 (Knapsack) | 44 | 27 | 38.64 | 32.88 | 0 | 100 | 100 | 0.33 | 7 |
| CK | 35 | 32 | 8.57 | – | 32 | 8.57 | – | 5.04 | 107 |
Sheath Blight Control
The agricultural UAV demonstrated superior suppression of sheath blight (Table 4), reducing disease incidence and severity more effectively than knapsack spraying by 14 DPA.
| Treatment | Plants Surveyed | Pre-Treatment | 14 DPA | Control Efficacy (%) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Grade 1 | Grade 3 | Grade 5 | Grade 7 | Total Infected | Disease Index | Grade 1 | Grade 3 | Grade 5 | Grade 7 | Total Infected | Disease Index | |||
| T1 (UAV) | 342 | 18 | 2 | 2 | 0 | 22 | 1.1 | 14 | 0 | 0 | 0 | 14 | 0.45 | 92.33 |
| T2 (Knapsack) | 356 | 28 | 4 | 2 | 2 | 36 | 2.0 | 29 | 2 | 1 | 0 | 32 | 1.25 | 88.29 |
| CK | 352 | 38 | 2 | 1 | 0 | 41 | 1.55 | 50 | 32 | 12 | 8 | 102 | 8.27 | – |
Operational Efficiency and Cost
The agricultural UAV demonstrated significantly higher field efficiency and lower operational costs:
- UAV Efficiency: 1,140 m²/min
- Knapsack Efficiency: 8,004 m²/day (8-hour basis)
- UAV Cost: ~$1.50 USD/667m²
- Knapsack Cost: ~$3.00 USD/667m²
Transient leaf curling occurred at UAV turning points (resolved within 48 hours), with no significant environmental impact.
Discussion
The superior early efficacy (3 DPA) of the agricultural UAV against planthoppers can be attributed to the downdraft effect, which drives droplets into the lower and middle rice canopy where these pests reside. This contrasts with knapsack spraying, which primarily deposits chemicals on upper foliage. For leaf rollers (upper canopy pests), knapsack’s higher water volume initially provided better coverage of larval shelters, though the UAV achieved comparable control by 7 DPA and superior leaf protection by 14 DPA.
The agricultural UAV’s outstanding sheath blight control stems from enhanced droplet penetration reaching the stem base and leaf undersides—critical infection sites. The downdraft effect significantly improves fungicide deposition in these zones compared to conventional methods. The observed transient phytotoxicity at turning points highlights the need for optimized flight path planning and parameter adjustments to avoid localized over-application.
Integrating agricultural drones with precision technologies like multispectral sensors and AI-driven path planning (e.g., genetic algorithms, neural networks) offers potential for further optimization. These systems enable dynamic prescription mapping and variable-rate application, potentially reducing agrochemical usage by over 30% while maintaining efficacy.
Conclusion
Agricultural drones provide a technically superior and economically advantageous solution for rice pest and disease management. Key benefits include:
- Rapid onset of insecticidal action, particularly against lower-canopy pests
- Enhanced fungicide efficacy against stem-base diseases
- Operational efficiency enabling timely large-scale interventions
- 50% reduction in application costs compared to knapsack spraying
- Reduced environmental footprint through precise chemical placement
With continuous advancements in UAV technology, nozzle design, electrostatic spraying, and intelligent control systems, agricultural drones are poised to become the cornerstone of sustainable, precision crop protection in global rice production systems.